Comparing Arctic Sea Ice Model Simulations to Satellite observations by Multiscale Directional Analysis of Sea Ice Deformation

Sea ice models have become essential components of weather, climate and ocean models. The reliability of process studies, environmental forecasts and climate projections alike depend on a realistic representation of sea ice. Developing and evaluating sea ice models requires methods for both large scales and fine-scale geomorphological structures such as linear kinematic features (LKF). We introduce a Multiscale Directional Analysis (MDA) method that diagnoses distributions of LKF orientation and intersection angles. The MDA method is different from previous methods in that it (a) takes into account the width of LKFs instead of estimating the orientation of centerlines; (b) separates curve-like features from point-like features providing the opportunity to reach a unified definition of LKF in both numerical and observational fields; (c) estimates scale-dependent intersection angles

Predictability of Deformation Features in Arctic Sea Ice

Sea ice deformation localizes along Linear Kinematic Features (LKFs) that are relevant for the air/ocean/sea-ice interaction and for shipping andmarine operations. At high resolution (< 5km) viscous-plastic sea ice models start to resolve LKFs. Here, we study the short-range (up to 10 days) potential predictability of LKFs in Arctic sea ice using ensemble simulations of an ocean/sea-ice model with a grid point separation of 4.5 km. We analyze the sensitivity of predictability to idealized initial perturbations, mimicking the uncertainties in sea ice analyses, and to growing uncertainty of the atmospheric forcing caused by the chaotic nature of the atmosphere. The similarity between pairs of ensemble members is quantified by Pearson correlation and Modified Hausdorff Distance (MHD). In our perfect model experiments, the potential predictability of LKFs, based on the MHD, drops below 0.6 after 4 days in winter. We find that forcing uncertainty (due to limited atmospheric predictability) largely determines LKF predictability on the 10-day time scale, while uncertainties in the initial state impact the potential predictability only within the first 4 days

The impact of advection schemes on restratifiction due to lateral shear and baroclinic instabilities

This paper quantifies spurious dissipation and mixing of various advection schemes in idealised experiments of lateral shear and baroclinic instabilities in numerical simulations of a re-entrant Eady channel for configurations with large and small Rossby numbers. In addition, a two-dimensional barotropic shear instability test case is used to examine numerical dissipation of momentum advection in isolation, without any baroclinic effects. Effects of advection schemes on the evolution of background potential energy and the dynamics of the restratification process are analysed. The advection schemes for momentum and tracers are considered using several different methods including a recently developed local dissipation analysis. As highly accurate but computationally demanding schemes we apply WENO and MP5, and as more efficient lower-order total variation diminishing (TVD) schemes we use among others the SPL-max-View the MathML source13 and a third-order-upwind scheme. The analysis shows that the MP5 and SPL-max-View the MathML source13 schemes provide the most accurate results. Following our comprehensive analysis of computational costs, the MP5 scheme is approximately 2.3 times more expensive in our implementation. In contrast to the configuration with a small Rossby number, in which significant differences between schemes are apparent, the different advection schemes behave similarly for a larger Rossby number. Regions of high numerical dissipation are shown to be associated with low grid Reynolds numbers. The major outcome of the present study is that generally positive global numerical dissipation and positive background potential energy evolution delay the restratification process

A framework to model thermomechanical coupled of fracture and martensite transformation in austenitic microstructures

A fully thermomechanical coupled phase-field (PF) model is presented to investigate the mechanism of austenite-to-martensite phase transformation (MPT) and crack initiation as well as its propagation in pure austenitic microstructures. The latent heat release and absorption involved in the MPT are explicitly taken into account by coupling the PF model with transient latent heat transfer. In order to consider temperature dependency in the PF model for MPT, a temperature-dependent Landau polynomial function, whose parameters are identified using molecular dynamics (MD) simulations, is proposed. Furthermore, the fracture surface energy is approximated based on the second-order PF model and then, the temporal evolution of the damage variable is given by the variational derivative of the total potential free energy of the system with respect to the damage variable. The achieved numerical results demonstrate that the model can be employed to predict the fracture mechanism of austenitic microstructures under a thermomechanical field in a multiphysics environment. The results reveal that the temperature has a tremendous impact on the growth rate of both martensitic variants and consequently on the crack growth path. The key contributions of this work are to shed light on the impact of thermal boundary conditions on the coupled process of MPT, crack initiation and growth

Potential Predictability of Arctic sea-ice linear kinematic features in high-resolution ensemble simulation

Linear kinematic features (LKFs) in sea ice, potentially important for short-term forecasts and for climate simulations, emerge as viscous-plastic sea ice models are used at high resolution (~ 4.5 km). Here we analyze the short-range (up to 10 days) potential predictability of LKFs in Arctic sea ice using an ocean/sea-ice model with a grid point separation of 4.5 km. We analyze the sensitivity of predictability to idealized initial perturbations, mimicking the uncertainties in sea ice analyses, and to growing uncertainty of the atmospheric forcing caused by the chaotic nature of the atmosphere. For the latter we use different members of ECMWF ensemble forecasts to drive ocean/sea-ice forecasts. For our analysis, we diagnose LKFs occurrence and investigate different sea ice characteristics. We find that forcing uncertainty (due to limited atmospheric predictability) largely determines LKF predictability on the 10-day time scale. When it comes to metrics, we demonstrate that spatial correlation, although a useful metric to measure some aspects of deformation field similarity, fails to detect LKF similarity when LKFs are only slightly shifted in space. The Modified Hausdorff Distance (MHD) appears to be a more appropriate metric, but it can be misleading if the LKF density is very high, for example due to artificial LKFs caused by spurious small-scale perturbations of the sea-ice initial state

Anti-plane interfacial crack with functionally graded coating: static and dynamic

The anti-plane displacement discontinuity method is applied to establish the Fredholm integral equation of the first kind for the orthotropic Functionally Graded Material (FGM) coatings subjected to static/dynamic shears. The shear modulus and mass density are assumed to vary exponentially through the thickness. The static and dynamic fundamental solutions with anti-plane displacement discontinuity are derived for orthotropic FGM coating by using Fourier transform method and Laplace transform method. It has been shown that the transformed fundamental solution with orthotropic coatings has the same order of hyper-singularity as in the static case, i.e. O(1/r2), and the Chebyshev polynomials of the second kind are used to solve the integral equations numerically. The time dependent stress intensity factors are obtained directly from the coefficients of the Chebyshev polynomials with the aid of Durbin’s Laplace transform inversion method. A comparative study of FGM versus homogeneous coating is conducted, and the dependence of the stress intensity factors in the coating/substrate system on the material property (orthotropic) and thickness of coating is examined. Two examples including the static/dynamic loads are given as benchmarks for the numerical methods and application in composite engineering

Bright Prospects for Arctic Sea Ice Prediction on Subseasonal Time Scales

With retreating sea ice and increasing human activities in the Arctic come a growing need for reliable sea ice forecasts up to months ahead. We exploit the subseasonal‐to‐seasonal prediction database and provide the first thorough assessment of the skill of operational forecast systems in predicting the location of the Arctic sea ice edge on these time scales. We find large differences in skill between the systems, with some showing a lack of predictive skill even at short weather time scales and the best producing skillful forecasts more than 1.5 months ahead. This highlights that the area of subseasonal prediction in the Arctic is in an early stage but also that the prospects are bright, especially for late summer forecasts. To fully exploit this potential, it is argued that it will be imperative to reduce systematic model errors and develop advanced data assimilation capacity

Evaluating effects of southern yellow pine biochar and wood vinegar on poultry litter

The objectives of this study were to investigate nutrient retention, intI1 prevalence, and compost maturity rates for poultry litter co-composted with 5, 10, and 20% southern yellow pine biochar and with or without 2% wood vinegar (WV). Samples were collected at 0, 57, and 112 days to measure nitrogen, phosphorus, and potassium (N, P, K) concentrations, microbial counts, pH, moisture content, carbon to nitrogen (C:N) ratio, and intI1 abundance. Composts were aerated once a week and the temperature was also recorded once a week. There was sufficient rainfall so no additional water was added. The results showed that N and P concentrations significantly increased over time in all treatments except 20% biochar and 20% biochar + wood vinegar, while K concentrations significantly decreased. In general, composting with wood vinegar significantly decreased nutrient concentrations; however, all nutrient concentrations were much higher than typical animal manure fertilizers. Increases in biochar level resulted in significantly lower bacteria counts and significantly higher fungi counts. Compost treatments containing wood vinegar had significantly lower bacteria and fungi counts, indicating that southern yellow pine wood vinegar had a biocide effect on microorganisms, and may be not suitable for composting at that application rate. intI1 prevalence was not significantly different among treatments, which may be due to insufficient thermophilic composting. Because thermophilic temperatures were not achieved, the compost was not mature by the end of the study; therefore, compost maturity rates could not be determined

Continuous discontinuities: comparing observed and modelled sea ice deformation features

The Arctic is highly sensitive to changes in the global climate. One of the most prominent examples in this context is the shrinking sea ice cover over the past decades. The impact of the change in ice coverage on the global climate requires a thorough understanding of ice dynamics, as drifting sea ice transports salt and heat and in this way influences ocean dynamics. Sea ice motion is mainly driven by wind, ocean currents and internal ice stress. Convergent ice motion causes features such as ridges and rubble fields, which change the momentum exchange between atmosphere, ice and ocean. Openings in the ice due to divergent motion increase the exchange of heat and matter between ocean and atmosphere. On time scales of days to weeks, linear kinematic features, such as leads and ridges, evolve on spatial scales ranging from meters to tens and hundreds of kilometers. These features also emerge in numerical sea ice models when the resolution of the simulations is increased to a few kilometers. While plausible, their realism in the simulations is yet unclear and requires a detailed evaluation, with the help of (in our case satellite-based) observations. We use Arctic-wide MITgcm simulations for 2006 at a spatial resolution of approximately 4km for a regional comparison with microwave satellite observations, e.g. from Synthetic Aperture Radar (SAR). We derive sea ice displacement from a sequence of satellite images by measuring the offset between matching patterns in different images. Discontinuities in the resulting velocity field indicate regions of instantaneous deformation that occur at some point in the time interval between the acquisition of the two SAR images used for displacement retrieval. The obtained quantities of deformation by divergence, shear and vorticity are scale-dependent. As a consequence, they depend on the spatial resolution of the SAR images and differ from the quantities calculated by the model. Hence, the comparison between model simulations and results of retrievals from remote sensing data is not straightforward. Therefore, we pay special attention to the spatial and temporal scales of the observed / modelled processes and introduce appropriate statistical tools. By evaluating the kinematic features in the results of high-resolution sea ice models based on the microwave remote sensing data we expect to be able to assess and improve the ice rheology in these sea ice models